> ## Documentation Index
> Fetch the complete documentation index at: https://docs.levelrail.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Self-host Jupyter GPU Notebook with Docker

> JupyterLab with a CUDA-ready data science stack for training and experimenting with models.

JupyterLab with a CUDA-ready data science stack for training and experimenting with models.

This page describes the Levelrail template for Jupyter GPU Notebook (AI). It deploys the services below as one Docker Compose app on your own server. Project site: [https://github.com/iot-salzburg/gpu-jupyter](https://github.com/iot-salzburg/gpu-jupyter).

Recommended memory: about 4096 MiB.

<Warning>This template reserves an NVIDIA GPU, so it needs a node with a GPU and the NVIDIA container runtime.</Warning>

## Services, ports and volumes

| Service | Image | Container ports | Volumes |
| - | - | - | - |
| `jupyter` | `cschranz/gpu-jupyter:v1.11_cuda-13.0_ubuntu-24.04_python-only` | 8888 | `jupyter_work -&#62; /home/jovyan/work` |

## Environment variables

| Service | Variable | Value |
| - | - | - |
| `jupyter` | `JUPYTER_TOKEN` | Generated at deploy |

Passwords and keys marked as generated are created for you when the app is deployed and stored as secrets. Values are not shown here.

## Deploy Jupyter GPU Notebook with Levelrail

In the dashboard, open **Apps**, choose **New app**, then **Browse templates**, and select Jupyter GPU Notebook. Review the Compose body and deploy.

With the CLI:

```bash theme={"dark"}
levelrail-cli templates deploy jupyter-gpu --name my-jupyter-gpu
```

See the [service template catalog](/templates-and-registry) for how templates work, and [Getting started](/getting-started) if you have not installed Levelrail yet.

## More AI templates

* [AnythingLLM](/self-host/anythingllm)
* [ComfyUI](/self-host/comfyui)
* [Flowise](/self-host/flowise)
* [Flowise (Postgres + Qdrant)](/self-host/flowise-postgres)
* [Label Studio](/self-host/label-studio)

All templates are listed in the [self-host gallery](/self-host).


This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.